{"id":3466834,"url":"https://alion.io/job/dataforest-middle-data-engineer","title":"Middle+ Data Engineer","company":{"id":2340519,"name":"DATAFOREST","domain":"dataforest.ai","url":"https://alion.io/company/dataforest-ai","size_band":null,"is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Ukraine"],"countries":["UA"],"hiring_countries":["UA"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":18500,"max_usd":50000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1015},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Boto3","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Cassandra","optional":true},{"name":"Databricks","optional":true},{"name":"Pandas","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Redis","optional":true},{"name":"ScyllaDB","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-05T09:40:33Z","employer_posted_date":null,"last_verified_at":"2026-10-05T09:40:33Z","board_verified":false,"closed_at":null,"days_open":28,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":28},"description":"Dataforest is looking for a Data Engineer to join an interesting software development project in the field of Cybersecurity. Our client’s platform offers Identity Insights drives real-time, multi-contextual digital forensics to protect new account opening workflows and expose fake accounts already in a customer database.\n\nYou'll be a great fit if you have:\n\n- 3+ years of hands on in data engineering;\n\n- 3+ years of commercial experience with Python;\n\n- Advanced experience with SQL DBs (optimisations, monitoring, etc.);\n\n- Advanced experience with PySpark;\n\n- Solid understanding of ETL principles (architecture/ monitoring/ alerting/search and resolve bottlenecks);\n\n- Familiar with AWS infrastructure (boto3, S3 buckets, etc);\n\n- Experience working with large volumes of data;\n\n- Understanding the principles of medallion architecture.\n\nWould be a plus:\n\n- Cassandra/Scylla\n\n- PostgreSQL\n\n- Pandas\n\n- Experience with Kafka and Redis\n\nWhat you'll do:\n\n- Maintain data processing architecture using Python and PySpark that interacts with ScyllaDB & PostgreSQL.\n\n- Work with Databricks 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